[refactor]: remove VideoGenerator.generate_video

VideoGenerator.generate(request) is the one inference entry point. The
generate_video keyword call, its mapping from flat keywords to a request
(legacy_generate_call_to_request and its helpers), and the tests of that
mapping are removed. Comments and docs that named generate_video describe
generate and request extensions instead.

scripts/ltx2_sr_alignment.py keeps its generate_video call, because its
reference run imports the separate FastVideo-internal package.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012M91wnVFmPEvJ9h39r5BH7

examples/inference/optimizations/qad_fp4_ab.py

@@ -192,9 +192,7 @@ def main() -> None:
         last = _generate()
         torch.cuda.synchronize()
         wall = time.perf_counter() - t0
-        # generate_video returns a plain dict; attribute access would always
-        # fall back to wall time.
-        gen_t = last.get("generation_time") if isinstance(last, dict) else None
+        gen_t = last.generation_time
         denoise_times.append(gen_t if gen_t is not None else wall)
         print(f"[qad] {tag} run {i + 1}/{runs}: {wall:.2f}s wall "
               f"(gen {denoise_times[-1]:.2f}s)")

examples/inference/optimizations/torch_compile_example.py

@@ -47,8 +47,8 @@ def main() -> None:
 
     def _run(tag: str) -> float:
         save = tag == "measured"
-        # Modern typed-request API (generate_video is deprecated). Same
-        # prompt/seed/shapes both runs so the compiled graph is reused.
+        # Typed request API. Same prompt/seed/shapes both runs so the
+        # compiled graph is reused.
         request: dict = {
             "prompt": PROMPT,
             "sampling": {